def test_automatically_finds_variables(df_vartypes): # test case 1: automatically select variables transformer = BoxCoxTransformer(variables=None) X = transformer.fit_transform(df_vartypes) # expected output transf_df = df_vartypes.copy() transf_df["Age"] = [9.78731, 10.1666, 9.40189, 9.0099] transf_df["Marks"] = [-0.101687, -0.207092, -0.316843, -0.431788] # test init params assert transformer.variables is None # test fit attr assert transformer.variables_ == ["Age", "Marks"] assert transformer.n_features_in_ == 5 # test transform output pd.testing.assert_frame_equal(X, transf_df) # test inverse_transform Xit = transformer.inverse_transform(X) # convert numbers to original format. Xit["Age"] = Xit["Age"].round().astype("int64") Xit["Marks"] = Xit["Marks"].round(1) # test pd.testing.assert_frame_equal(Xit, df_vartypes)
def test_automatically_finds_variables(df_vartypes): # test case 1: automatically select variables transformer = BoxCoxTransformer(variables=None) X = transformer.fit_transform(df_vartypes) # expected output transf_df = df_vartypes.copy() transf_df["Age"] = [9.78731, 10.1666, 9.40189, 9.0099] transf_df["Marks"] = [-0.101687, -0.207092, -0.316843, -0.431788] # test init params assert transformer.variables == ["Age", "Marks"] # test fit attr assert transformer.input_shape_ == (4, 5) # test transform output pd.testing.assert_frame_equal(X, transf_df)